Webpage texts are often emphasized by decorations such as bold, italic, underline, and text color using HTML (HyperText Markup Language) tags and CSS (Cascading Style Sheets). However, users with visual impairment often struggle to recognize decorations appropriately because most screen readers do not read decorations appropriately. To overcome this limitation, we propose a method to read emphasized texts by changing the reading voice parameters of a screen reader and adding sound effects. First, the strong emphasis types and reading voices are investigated. Second, the intensity of the emphasis type is used to calculate a score. Then the score is used to assign the reading method for the emphasized text. Finally, the proposed method is evaluated by users with and without visual impairment. The proposed method can convey emphasized texts, but future improvements are necessary.

The increase in the time required for data processing, mask drawing, and inspection of photomask, has led to substantial increase in mask manufacturing cost. This has become one of the major challenges in the semiconductor industry. We have developed a data flow process for mask manufacturing in which we refer to design intent information in order to reduce TAT of mask manufacturing processes. We convert design level information "Design Intent (DI)" into priority information of mask manufacturing data known as "Mask Data Rank (MDR)" so that we can identify and sort out the importance of mask patterns from the view point of the design side. As a result, we can reduce mask writing time and mask inspection time. Our objective is to build efficient data flow conversion system from DI to MDR. In this paper we introduce the idea of MDR and the software system that we built for DI extraction. Then we show the experimental results with actual chip data. Lastly we will discuss related issues and their solutions.